DBMS > Blueflood vs. JanusGraph vs. Kdb vs. SiteWhere vs. Snowflake

System Properties Comparison Blueflood vs. JanusGraph vs. Kdb vs. SiteWhere vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

Scalable TimeSeries DBMS based on Cassandra

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

High performance Time Series DBMS

M2M integration platform for persisting/querying time series data

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Time Series DBMS

Graph DBMS

Time Series DBMS
Vector DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Relational DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	0.06
Rank	#353	Overall
	#34	Time Series DBMS

Score	1.94
Rank	#129	Overall
	#12	Graph DBMS

Score	7.55
Rank	#53	Overall
	#3	Time Series DBMS
	#1	Vector DBMS

Score	0.06
Rank	#356	Overall
	#35	Time Series DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

blueflood.io

janusgraph.org

kx.com

github.com/sitewhere/sitewhere

www.snowflake.com

Technical documentation

github.com/rax-maas/blueflood/wiki

docs.janusgraph.org

code.kx.com

sitewhere1.sitewhere.io/index.html

docs.snowflake.net/manuals/index.html

Developer

Rackspace

Linux Foundation; originally developed as Titan by Aurelius

Kx Systems, a division of First Derivatives plc

SiteWhere

Snowflake Computing Inc.

Initial release

2013

2017

2000

kdb was released 2000, kdb+ in 2003

2010

2014

Current release

0.6.3, February 2023

3.6, May 2018

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache 2.0

commercial

free 32-bit version

Open Source

Common Public Attribution License Version 1.0

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

Server operating systems

Linux
OS X

Linux
OS X
Unix
Windows

Linux
OS X
Solaris
Windows

Linux
OS X
Windows

hosted

Data scheme

predefined scheme

yes

predefined scheme

yes

support of semi-structured data formats (JSON, XML, Avro)

Typing

predefined data types such as float or date

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

yes

Secondary indexes

yes

table attribute 'grouped'

SQL

Support of SQL

SQL-like query language (q)

yes

APIs and other access methods

HTTP REST

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket

HTTP REST

CLI Client
JDBC
ODBC

Supported programming languages

Clojure
Java
Python

C
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

user defined functions

Triggers

yes

with views

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

horizontal partitioning

Sharding

based on HBase

yes

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

yes

Source-replica replication

selectable replication factor

based on HBase

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

similar paradigm used for internal processing

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

User authentification and security via Rexster Graph Server

rights management via user accounts

Users with fine-grained authorization concept

Users with fine-grained authorization concept, user roles and pluggable authentication

More information provided by the system vendor

Specific characteristics

Integrated columnar database & programming system for streaming, real time and historical...
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Competitive advantages

provides seamless scalability; runs on industry standard server platforms; is top-ranked...
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Typical application scenarios

tick database streaming sensor data massive intelligence applications oil and gas...
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Key customers

Goldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
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Market metrics

kdb+ performance and reliability proven by our customers in critical infrastructure...
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Licensing and pricing models

upon request
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